The European community requires early stage researchers (ESRs) who can work across the boundaries of traditional disciplines, integrating experimental and in silico approaches to understand and manage highly prevalent multifactorial disorders, such as musculoskeletal disorders. The Disc4All training network utilises intervertebral disc degeneration (LDD) leading to low back pain (LBP) as a relevant application for the integration of data and computational simulations in translational medicine, to enable rational interpretations of the complexity of the interactions that eventually lead to symptoms.
LBP is the largest cause of morbidity worldwide, yet there remains controversy as to the specific cause leading to poor treatment options and prognosis. LDD is reported to account for 50% of LBP in young adults, but the interplay of factors from genetics, environmental, cellular responses and social and psychological factors is poorly understood. Unfortunately, the integration of such data into a holistic and rational map of degenerative processes and risk factors has not been achieved, requiring creation of professional cross-competencies, which current training programmes in biomedicine, biomedical engineering and translational medicine fail to address, individually.
Disc4All aims to tackle this issue through collaborative expertise of clinicians; computational physicists and biologists; geneticists; computer scientists; cell and molecular biologists; microbiologists; bioinformaticians; and industrial partners. It provides interdisciplinary training in data curation and integration; experimental and theoretical/computational modelling; computer algorithm development; tool generation; and model and simulation platforms to transparently integrate primary data for enhanced clinical interpretations through models and simulations. Complementary training is offered in dissemination; project management; research integrity; ethics; regulation; policy; business strategy; and public and patient engagement. The Disc4All ESRs will provide a new generation of internationally mobile professionals with unique skill sets for the development of thriving careers in translational research applied to multifactorial disorders.
This PhD project will address 3D modelling of the lumbar spine from medical images. Methods using deep learning and statistical modelling will be developed to segment the lumbar vertebrae and intervertebral disks in 3D MRI sequences and CT image, and provide 3D subject-specific lumbar spine models from 2D medical images (X-rays or mid-sagital MR images) used in clinical practices. Those methods will be used in combination with finite-element-based simulation methods to develop a diagnosis and predictive tool for intervertebral disk degeneration.
Type of contracts: temporary (36 months)
Job status: full-time
Hours per week: See individual job offers
Offer starting dates: Between November 1st, 2020 and January 31st, 2021
EU Research Framework: H2020 MSCA-ITN-ETN
Marie Curie Grant Agreement Number: 955735